{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8f4d2c76-8f6d-45a1-8b34-abcc625d31a0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\anaconda3\\Lib\\site-packages\\torch\\utils\\_pytree.py:185: FutureWarning: optree is installed but the version is too old to support PyTorch Dynamo in C++ pytree. C++ pytree support is disabled. Please consider upgrading optree using `python3 -m pip install --upgrade 'optree>=0.13.0'`.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.6.0+cpu\n",
      "None\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "#cpu版本的代码是在自己的笔记本上运行的结果\n",
    "import torch\n",
    "print(torch.__version__)\n",
    "print(torch.version.cuda)\n",
    "print(torch.cuda.is_available())  #输出为True，则安装无误"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ff806648-d569-4f36-a84e-37985f137b47",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = torch.arange(0,10)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d570724b-993b-4969-8c2c-2588108e4bd8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0, 2, 4, 6, 8])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = torch.arange(0,10,2)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "532a4e69-8fa6-41a1-b069-63175d7ce3da",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = torch.arange(12)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f3b44b6b-2f3a-4003-8d59-8b94321961ce",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\AppData\\Local\\Temp\\ipykernel_7964\\3143999027.py:1: UserWarning: torch.range is deprecated and will be removed in a future release because its behavior is inconsistent with Python's range builtin. Instead, use torch.arange, which produces values in [start, end).\n",
      "  x = torch.range(1,12)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12.])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = torch.range(1,12)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b140fffb-6b0a-4f1b-b04b-8afd962d6f2d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[ 1.,  2.,  3.,  4.],\n",
       "        [ 5.,  6.,  7.,  8.],\n",
       "        [ 9., 10., 11., 12.]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = x.reshape(3,4)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "55f07be2-0129-4d0e-88f1-d19ef2ef19b7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([3, 4])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f23af3b7-6f66-43d9-bff1-0814bfb79b10",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.numel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "80c1f1c5-8880-4ecc-9499-04fe2f68eb87",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.ndim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "9501c3fe-f406-46e7-b2cb-ce07efbf0eac",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.float32"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "78b683cc-6acd-4812-993f-5e4e94738fea",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'torch.Tensor'> tensor([ 1, 12, 20])\n",
      "<class 'torch.Tensor'> tensor([2, 4, 8])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([          1,       20736, 25600000000])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = torch.tensor([1,12,20])\n",
    "print(type(a),a)\n",
    "\n",
    "b = torch.tensor([2,4,8])\n",
    "print(type(a),b)\n",
    "\n",
    "a**b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4052cb43-b3b7-4f3e-8236-0fd62d68005f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float32(9.0)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "2b40ea9c-814c-486d-98f7-c59991cf3fb4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([False, False, False])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a == b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1e27746e-b2e8-4665-89cf-5a5ff7509175",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[0., 0., 0.],\n",
      "        [0., 0., 0.],\n",
      "        [0., 0., 0.]])\n",
      "tensor([[1., 1., 1.],\n",
      "        [1., 1., 1.],\n",
      "        [1., 1., 1.]])\n",
      "tensor([[0., 0., 0.],\n",
      "        [0., 0., 0.],\n",
      "        [0., 0., 0.],\n",
      "        [1., 1., 1.],\n",
      "        [1., 1., 1.],\n",
      "        [1., 1., 1.]])\n",
      "tensor([[0., 0., 0., 1., 1., 1.],\n",
      "        [0., 0., 0., 1., 1., 1.],\n",
      "        [0., 0., 0., 1., 1., 1.]])\n"
     ]
    }
   ],
   "source": [
    "a = torch.zeros(3,3)\n",
    "print(a)\n",
    "\n",
    "b = torch.ones(3,3)\n",
    "print(b)\n",
    "\n",
    "x = torch.cat((a,b),dim=0)\n",
    "print(x)\n",
    "x= torch.cat((a,b),dim=1)\n",
    "print(x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "504afd18-9367-4d5b-b021-bb14fd85057c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'torch.Tensor'>\n",
      "tensor([[0., 0., 0., 1., 1., 1.],\n",
      "        [0., 0., 0., 1., 1., 1.],\n",
      "        [0., 0., 0., 1., 1., 1.]])\n",
      "<class 'numpy.ndarray'>\n",
      "[[0. 0. 0. 1. 1. 1.]\n",
      " [0. 0. 0. 1. 1. 1.]\n",
      " [0. 0. 0. 1. 1. 1.]]\n"
     ]
    }
   ],
   "source": [
    "print(type(x))\n",
    "print(x)\n",
    "x = x.numpy()\n",
    "print(type(x))\n",
    "print(x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "61ab39f8-03ea-4c38-85e9-cb3aa643b75d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'torch.Tensor'> tensor(3.5000)\n"
     ]
    }
   ],
   "source": [
    "x = torch.tensor(3.5)\n",
    "print(type(x),x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "12ac6246-5d2f-45ea-b50f-3c8664ecaff8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'torch.Tensor'> tensor([3.5000])\n"
     ]
    }
   ],
   "source": [
    "x = torch.tensor([3.5])\n",
    "print(type(x),x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3954a64a-8ae5-48fd-af65-d7b1fea1ec3c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'float'> 3.5\n"
     ]
    }
   ],
   "source": [
    "print(type(x.item()),x.item())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d0e7e297-4557-4904-9091-4d7e12ed892e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.26.4\n",
      "2.2.0\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "print(np.__version__)  # 输出 numpy 版本\n",
    "print(pd.__version__)  # 输出 pandas 版本"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "76862a62-2618-4de3-abf1-716a7cf2e5a3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.0.10\n"
     ]
    }
   ],
   "source": [
    "import openpyxl\n",
    "print(openpyxl.__version__)  # 应输出 ≥3.1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "edb762e3-e78f-43aa-8d07-ad7533a4d67f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.1.5\n"
     ]
    }
   ],
   "source": [
    "import openpyxl\n",
    "print(openpyxl.__version__)  # 应输出 ≥3.1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f6977a63-dfe4-4821-9db8-fed7b6166082",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x243a95a03d0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#用Matplotlib绘制，实现广告投放与收益关系的线性回归\n",
    "投放=[200,400,800,1500]\n",
    "收益=[270,700,1100,2100]\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.family'] = 'SimHei'  #中文支持\n",
    "\n",
    "plt.title(\"广告投资与收益关系的线性回归\")  #图表的标题\n",
    "plt.xlabel(\"广告收益\")       #x轴标题\n",
    "plt.ylabel(\"投放金额\")   #y轴标题\n",
    "\n",
    "\n",
    "plt.xticks(range(0,2000,100))  #x轴刻度\n",
    "plt.yticks(range(0,3000,100))  \n",
    "\n",
    "plt.scatter(投放,收益)\n",
    "#plt.plot(投放,收益,'red')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e31ee98c-9cac-4b0d-bc93-e7b2b9652997",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x243a9b9ba10>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#用Matplotlib绘制，实现广告投放与收益关系的线性回归\n",
    "投放=[200,400,800,1500]\n",
    "收益=[270,700,1100,2100]\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.family'] = 'SimHei'  #中文支持\n",
    "\n",
    "plt.title(\"广告投资与收益关系的线性回归\")  #图表的标题\n",
    "plt.xlabel(\"广告收益\")       #x轴标题\n",
    "plt.ylabel(\"投放金额\")   #y轴标题\n",
    "\n",
    "\n",
    "plt.xticks(range(0,2000,100))  #x轴刻度\n",
    "plt.yticks(range(0,3000,100))  \n",
    "\n",
    "plt.scatter(投放,收益)\n",
    "#plt.plot(投放,收益,'red')\n",
    "def function_y(x,w,b):\n",
    "    y = []\n",
    "    for i in range(len(x)):\n",
    "        y.append( w*x[i]+b)\n",
    "    return y\n",
    "\n",
    "w = 1.22\n",
    "b = 160\n",
    "xx = [100,300,700,1000,1300,1700] \n",
    "yy = function_y(xx,w,b)\n",
    "plt.plot(xx,yy,'green')\n",
    "\n",
    "w = 1\n",
    "b = 270\n",
    "yy = function_y(xx,w,b)\n",
    "plt.plot(xx,yy,'red')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "64aae1a9-e6f7-46ea-abe8-824ca80cd902",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x243a9c17750>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#用Matplotlib绘制，表现损失与权重关系\n",
    "def MSE_Loss(list_x,list_y,w,b):\n",
    "    list_loss = []\n",
    "    for i in range(len(list_x)): \n",
    "        loss = (list_y[i] - (list_x[i]*w+b))** 2\n",
    "        list_loss.append(loss)\n",
    "    #print(list_loss)\n",
    "    return 1/len(list_loss)*sum(list_loss)\n",
    "\n",
    "投放=[200,400,800,1500]\n",
    "收益=[270,700,1100,2100]\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.family'] = 'SimHei'  #中文支持\n",
    "\n",
    "plt.title(\"权重值w和损失loss的关系\")  #图表的标题\n",
    "plt.xlabel(\"权重值w\")       #x轴标题\n",
    "plt.ylabel(\"损失loss\")   #y轴标题\n",
    "\n",
    "\n",
    "def func_list_MES(w):\n",
    "    list_MES= []\n",
    "    for i in range(len(w)):\n",
    "        list_MES.append(MSE_Loss(投放,收益,w[i],170))\n",
    "        \n",
    "    return list_MES\n",
    "#x轴是权重w的大小，从1.1一直测试到1.3，用小数点后三位\n",
    "x = np.arange(1.2,1.3,0.001)\n",
    "y = func_list_MES(x)\n",
    "plt.plot(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "44f95c16-c7b3-4fed-8064-861a1b680ab0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1d376e66a90>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#用Matplotlib绘制，实现广告投放与收益关系的线性回归\n",
    "投放=[200,400,800,1500]\n",
    "收益=[270,700,1100,2100]\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.family'] = 'SimHei'  #中文支持\n",
    "\n",
    "plt.title(\"广告投资与收益关系的线性回归\")  #图表的标题\n",
    "plt.xlabel(\"广告收益\")       #x轴标题\n",
    "plt.ylabel(\"投放金额\")   #y轴标题\n",
    "\n",
    "\n",
    "plt.xticks(range(0,2000,100))  #x轴刻度\n",
    "plt.yticks(range(0,3000,100))  \n",
    "\n",
    "plt.scatter(投放,收益)\n",
    "#plt.plot(投放,收益,'red')\n",
    "def function_y(x,w,b):\n",
    "    y = []\n",
    "    for i in range(len(x)):\n",
    "        y.append( w*x[i]+b)\n",
    "    return y\n",
    "\n",
    "w = 1.22\n",
    "b = 160\n",
    "xx = [100,300,700,1000,1300,1700] \n",
    "yy = function_y(xx,w,b)\n",
    "plt.plot(xx,yy,'green')\n",
    "\n",
    "w = 1\n",
    "b = 270\n",
    "yy = function_y(xx,w,b)\n",
    "plt.plot(xx,yy,'red')\n",
    "\n",
    "w = 1.3845\n",
    "b = 23.1234\n",
    "yy = function_y(xx,w,b)\n",
    "plt.plot(xx,yy,'black')\n",
    "\n",
    "w = 1.3577\n",
    "b = 58.3521\n",
    "yy = function_y(xx,w,b)\n",
    "plt.plot(xx,yy,'yellow')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ab5a6fd0-8054-4d9f-9328-8d161e383b73",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最终参数：w = 1.3577, b = 58.1521\n",
      "预测函数：Revenue = 1.3577 * Spend + 58.1521\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 数据标准化处理（新增类型转换）\n",
    "advertising_spend = torch.tensor([200, 400, 800, 1500], dtype=torch.float32).view(-1, 1)\n",
    "revenue = torch.tensor([270, 700, 1100, 2100], dtype=torch.float32).view(-1, 1)\n",
    "\n",
    "# 转换为Python数值（关键修改）\n",
    "spend_mean = advertising_spend.mean().item()\n",
    "spend_std = advertising_spend.std().item()\n",
    "revenue_mean = revenue.mean().item()\n",
    "revenue_std = revenue.std().item()\n",
    "\n",
    "#print(f\"spend_mean={spend_mean},spend_std={spend_std}\")\n",
    "#print(f\"revenue_mean={revenue_mean},revenue_std={revenue_std}\")\n",
    "# 标准化数据\n",
    "advertising_spend_normalized = (advertising_spend - spend_mean) / spend_std\n",
    "revenue_normalized = (revenue - revenue_mean) / revenue_std\n",
    "#print(f\"advertising_spend_normalized={advertising_spend_normalized},revenue_normalized={revenue_normalized}\")\n",
    "\n",
    "class LinearRegression(nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.linear = nn.Linear(1, 1)\n",
    "\n",
    "    def forward(self, x):\n",
    "        return self.linear(x)\n",
    "\n",
    "model = LinearRegression()\n",
    "criterion = nn.MSELoss()\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.1) \n",
    "\n",
    "epochs = 100\n",
    "loss_history = []\n",
    "w_history = []\n",
    "b_history = []\n",
    "\n",
    "for epoch in range(epochs):\n",
    "    predictions = model(advertising_spend_normalized)\n",
    "    loss = criterion(predictions, revenue_normalized)\n",
    "    \n",
    "    optimizer.zero_grad()\n",
    "    loss.backward()\n",
    "    optimizer.step()\n",
    "    \n",
    "    loss_history.append(loss.item())\n",
    "    w_history.append(model.linear.weight.data.item())\n",
    "    b_history.append(model.linear.bias.data.item())\n",
    "\n",
    "# 反标准化参数（保持不变）\n",
    "final_w = model.linear.weight.data.item() * (revenue_std / spend_std)\n",
    "final_b = model.linear.bias.data.item() * revenue_std + revenue_mean - final_w * spend_mean\n",
    "\n",
    "# 可视化部分（修改预测值计算方式）\n",
    "plt.figure(figsize=(15, 5))\n",
    "\n",
    "# 绘制图1. 损失曲线（保持不变）\n",
    "plt.subplot(1, 3, 1)\n",
    "plt.plot(loss_history)\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('MSE Loss')\n",
    "plt.title('Training Loss Convergence')\n",
    "plt.grid(True)\n",
    "\n",
    "# 绘制图2. 参数更新轨迹（保持不变）\n",
    "plt.subplot(1, 3, 2)\n",
    "plt.scatter(w_history, b_history, c=range(epochs), cmap='viridis', s=10)\n",
    "plt.colorbar(label='Epoch')\n",
    "plt.xlabel('Weight (w)')\n",
    "plt.ylabel('Bias (b)')\n",
    "plt.title('Parameter Optimization Trajectory')\n",
    "plt.grid(True)\n",
    "\n",
    "# 绘制图3. 数据拟合效果（修改为直接使用原始参数计算）\n",
    "plt.subplot(1, 3, 3)\n",
    "plt.scatter(advertising_spend.numpy(), revenue.numpy(), label='Actual Data')\n",
    "\n",
    "# 使用原始参数生成预测值（关键修改）\n",
    "x_vals = np.linspace(150, 1550, 100).reshape(-1, 1)  # 生成更平滑的曲线\n",
    "y_pred = final_w * x_vals + final_b\n",
    "plt.plot(x_vals, y_pred, color='red', label='Fitted Line')\n",
    "\n",
    "plt.xlabel('Advertising Spend')\n",
    "plt.ylabel('Revenue')\n",
    "plt.title('Linear Regression Fit')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(f\"最终参数：w = {final_w:.4f}, b = {final_b:.4f}\")\n",
    "print(f\"预测函数：Revenue = {final_w:.4f} * Spend + {final_b:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c4bfe4d-1d13-4b1e-b6c4-915d4f9affb9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "\n",
    "dir(torch.nn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9ec2c415-ac63-48bb-a9ad-973e66e0f891",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on package torch.nn in torch:\n",
      "\n",
      "NAME\n",
      "    torch.nn - # mypy: allow-untyped-defs\n",
      "\n",
      "PACKAGE CONTENTS\n",
      "    _reduction\n",
      "    attention (package)\n",
      "    backends (package)\n",
      "    common_types\n",
      "    cpp\n",
      "    functional\n",
      "    grad\n",
      "    init\n",
      "    intrinsic (package)\n",
      "    modules (package)\n",
      "    parallel (package)\n",
      "    parameter\n",
      "    qat (package)\n",
      "    quantizable (package)\n",
      "    quantized (package)\n",
      "    utils (package)\n",
      "\n",
      "FUNCTIONS\n",
      "    factory_kwargs(kwargs)\n",
      "        Return a canonicalized dict of factory kwargs.\n",
      "        \n",
      "        Given kwargs, returns a canonicalized dict of factory kwargs that can be directly passed\n",
      "        to factory functions like torch.empty, or errors if unrecognized kwargs are present.\n",
      "        \n",
      "        This function makes it simple to write code like this::\n",
      "        \n",
      "            class MyModule(nn.Module):\n",
      "                def __init__(self, **kwargs):\n",
      "                    factory_kwargs = torch.nn.factory_kwargs(kwargs)\n",
      "                    self.weight = Parameter(torch.empty(10, **factory_kwargs))\n",
      "        \n",
      "        Why should you use this function instead of just passing `kwargs` along directly?\n",
      "        \n",
      "        1. This function does error validation, so if there are unexpected kwargs we will\n",
      "        immediately report an error, instead of deferring it to the factory call\n",
      "        2. This function supports a special `factory_kwargs` argument, which can be used to\n",
      "        explicitly specify a kwarg to be used for factory functions, in the event one of the\n",
      "        factory kwargs conflicts with an already existing argument in the signature (e.g.\n",
      "        in the signature ``def f(dtype, **kwargs)``, you can specify ``dtype`` for factory\n",
      "        functions, as distinct from the dtype argument, by saying\n",
      "        ``f(dtype1, factory_kwargs={\"dtype\": dtype2})``)\n",
      "\n",
      "FILE\n",
      "    d:\\programdata\\anaconda3\\lib\\site-packages\\torch\\nn\\__init__.py\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(torch.nn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bc166f7d-fdb1-47da-8c31-e1c0e51b94bb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(device(type='cpu'), device(type='cuda'), device(type='cuda', index=1))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "torch.device('cpu'),torch.device('cuda'),torch.device('cuda:1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c8ebf274-2ff0-40de-9818-ff4c76becc9a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.cuda.device_count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a7ce57bd-7ae3-4a86-94f3-b8641fdd1f23",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'torch.Tensor'>\n",
      "tensor([5.6700])\n",
      "cpu\n"
     ]
    }
   ],
   "source": [
    "x = torch.tensor([5.67])\n",
    "print(type(x))\n",
    "print(x)\n",
    "print(x.device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c53b7f34-a8db-4a9d-bb34-0d0e0eb50eb1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cpu\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "\n",
    "def try_gpu(i=0):\n",
    "    #如果存在gpu则返回gpu[i],否则返回cpu\n",
    "    if torch.cuda.device_count() >= i+1:\n",
    "        return torch.device(f'cuda{i}')\n",
    "    return torch.device('cpu')         \n",
    "    \n",
    "    \n",
    "x = torch.tensor([5.67],device=try_gpu())\n",
    "print(x.device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b831ff5c-fdd2-4e66-8763-f0f91c2ca611",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "\n",
    "net = torch.nn.Sequential(torch.nn.Linear(3,1))\n",
    "net = net.to(device=try_gpu())\n",
    "net(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9f55b967-0fe5-465b-8047-1be3ac882dcc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "device(type='cpu')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net[0].weight.data.device"
   ]
  }
 ],
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